Dexterous reaching, grasp transfer and planning using electrostatic representations

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

We propose a novel approach to transfer reach and grasp movements while being agnostic and invariant to finger kinematics, hand configurations and relative changes in object dimensions. We exploit a novel representation based on electrostatics to parametrise the salient aspects of the demonstrated grasp. By working in this alternate space that focuses on the relational aspects of the grasp rather than absolute kinematics, we are able to use inference based planning techniques to couple the motion in abstract spaces with trajectories in the configuration space of the robot. We demonstrate that our method computes stable grasps that generalise over objects of different shapes and robots of dissimilar kinematics while retaining the qualitative grasp type - all without expensive collision detection or re-optimisation.
Original languageEnglish
Title of host publicationHumanoid Robots (Humanoids), 2013 13th IEEE-RAS International Conference on
Pages211-218
Number of pages8
DOIs
Publication statusPublished - 1 Oct 2013

Keywords

  • dexterous manipulators
  • inference mechanisms
  • manipulator kinematics
  • planning (artificial intelligence)
  • collision detection
  • demonstrated grasp
  • dexterous reaching
  • dissimilar kinematics robots
  • electrostatic representations
  • finger kinematics
  • grasp transfer
  • hand configurations
  • inference based planning technique
  • robot configuration space
  • Computational modeling
  • Electric potential
  • Electrostatics
  • Grasping
  • Kinematics
  • Planning
  • Robots

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